IMPROVING LEARNING ABILITY OF RECURRENT NEURAL NETWORKS - Experiments on Speech Signals of Patients with Laryngopathies
Jarosław Szkoła, Krzysztof Pancerz, Jan Warchoł
2011
Abstract
Recurrent neural networks can be used for pattern recognition in time series data due to their ability of memorizing some information from the past. The Elman networks are a classical representative of this kind of neural networks. In the paper, we show how to improve learning ability of the Elman network by modifying and combining it with another kind of a recurrent neural network, namely, with the Jordan network. The modified Elman-Jordan network manifests a faster and more exact achievement of the target pattern. Validation experiments were carried out on speech signals of patients with laryngopathies.
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in Harvard Style
Szkoła J., Pancerz K. and Warchoł J. (2011). IMPROVING LEARNING ABILITY OF RECURRENT NEURAL NETWORKS - Experiments on Speech Signals of Patients with Laryngopathies . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011) ISBN 978-989-8425-35-5, pages 360-364. DOI: 10.5220/0003292603600364
in Bibtex Style
@conference{biosignals11,
author={Jarosław Szkoła and Krzysztof Pancerz and Jan Warchoł},
title={IMPROVING LEARNING ABILITY OF RECURRENT NEURAL NETWORKS - Experiments on Speech Signals of Patients with Laryngopathies},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011)},
year={2011},
pages={360-364},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003292603600364},
isbn={978-989-8425-35-5},
}
in EndNote Style
TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011)
TI - IMPROVING LEARNING ABILITY OF RECURRENT NEURAL NETWORKS - Experiments on Speech Signals of Patients with Laryngopathies
SN - 978-989-8425-35-5
AU - Szkoła J.
AU - Pancerz K.
AU - Warchoł J.
PY - 2011
SP - 360
EP - 364
DO - 10.5220/0003292603600364